Method and system for managing semiconductor manufacturing equipment

ABSTRACT

A management method capable of making an accurate decision about a malfunction of the semiconductor manufacturing equipment comprises the steps of: sampling a plurality of data of at least one parameter under normal operating condition of the semiconductor manufacturing equipment ( 11 ); generating a Mahalanobis space A from a group of sampled data; calculating a Mahalanobis distance D 2  from measured values of the parameter under ordinary operating condition of the semiconductor manufacturing equipment ( 11 ); and deciding that a malfunction occurred in the semiconductor manufacturing equipment ( 11 ) when the value of the Mahalanobis distance exceeds a predetermined value.

BACKGROUND OF THE INVENTION

[0001] 1. Field of the Invention

[0002] The present invention relates to a method and a system formanaging semiconductor manufacturing equipment.

[0003] 2. Related Art

[0004] In management systems for manufacturing equipment, such assemiconductor manufacturing equipment, to decide whether or not themanufacturing equipment is operating normally, an interlock system isgenerally adopted which detects data on a parameter such as thetemperature or pressure of the functional part of the manufacturingequipment, and stops the operation of the manufacturing equipment whenthe data indicates an abnormal value.

[0005] According to this interlock system, it is possible to immediatelystop the operation of the manufacturing equipment when an abnormal datavalue is detected, and thereby minimize the ejection of nonconformingproducts.

[0006] However, in a conventional interlock system such as mentionedabove, when the etching steps from beginning to end of etching work on aplasma etching system are controlled according to changes in the plasmaemission intensity, the plasma emission intensity varies greatly frombeginning to end of the etching process, so that the plasma emissionintensity cannot be used as a parameter to detect a malfunction of theequipment.

[0007] In the interlock system, only one decision is made whether or notdata values of a single parameter exceed a predetermined range, and itis impossible to capture time-series changes between data values.Therefore, it is not easy to catch a malfunction accurately.

[0008] Further, in the interlock system, even if a plurality ofparameters are combined, it is hard to give correlation between theparameters, and it is difficult to catch a malfunction accurately.

SUMMARY OF THE INVENTION

[0009] The object of the present invention is to provide a managementmethod and a management system capable of making a correct decisionabout a malfunction of the semiconductor manufacturing equipment.

[0010] According to the present invention, there is provided a method ofmanaging the operation of semiconductor manufacturing equipment,comprising sampling a plurality of data of at least one parameter underthe normal operating condition of the semiconductor manufacturingequipment, generating a Mahalanobis space from a group of sampled data,calculating a Mahalanobis distance from a group of measured values ofthe parameters, obtained under the operating condition of thesemiconductor manufacturing equipment by using the Mahalanobis space,and when the Mahalanobis distance exceeds a predetermined value, makinga decision that a malfunction occurred in the semiconductormanufacturing equipment.

[0011] In the management method according to the present invention, aMahalanobis space based on a data group including a plurality of data isformed, and by using this Mahalanobis space, a Mahalanobis distance iscalculated from measured values of the parameter, obtained in theoperating condition of the semiconductor manufacturing equipment, andaccording to the values of the Mahalanobis distance, a decision is madewhether the semiconductor manufacturing equipment is operating normallyor abnormally.

[0012] The above-mentioned Mahalanobis space is expressed by an inversematrix of a correlation matrix derived from an aggregate of data to bedescribed later. Therefore, by using a Mahalanobis space, even though asingle parameter is adopted, a data group is not handled as separatedata values in the Mahalanobis space, and a correlation among data istaken into consideration.

[0013] Consequently, according to the management method of the presentinvention, a decision can be made whether the operating condition of thesemiconductor manufacturing equipment is normal or not with highaccuracy not obtainable in the prior-art interlock system, in which thecorrelation among data is not considered. For this reason, the operationof the semiconductor manufacturing equipment can be managed with muchhigher accuracy than in the prior art.

[0014] Further, a plurality of parameters other than said at least oneparameter are provided. Mahalanobis spaces under abnormal conditions areformed previously, each abnormal condition being generated by settingone of said parameters at an abnormal value and other said parameters atnormal values. When, from a value of said Mahalanobis distance, adecision has been made that a malfunction occurred, Mahalanobisdistances corresponding to Mahalanobis spaces are calculated from saidmeasured values by using said Mahalanobis space under the abnormalcondition. And, it can be estimated that among said plurality ofparameters, abnormality occurred in a parameter that gave a Mahalanobisspace such that said Mahalanobis distance is closest to 1.

[0015] Among the Mahalanobis distances calculated on the basis of therespective Mahalanobis spaces, the Mahalanobis distance, which wascalculated by using a Mahalanobis space under a condition closest to thepresent condition that gave a measured value, is closest to 1.

[0016] Therefore, among a plurality of Mahalanobis spaces used forcalculating said Mahalanobis distances, a Mahalanobis space that broughtforth a Mahalanobis distance closest to the value 1 can be regarded asthe Mahalanobis space under a condition closest to the condition thatbrought forth the measured values. Accordingly, it can be estimated thatthe cause of abnormality lies in the abnormality detection parameterthat brought about a Mahalanobis space that produces a Mahalanobisdistance closest to the value 1.

[0017] The above-mentioned at least one parameter can be composed of aplurality of mutually different parameters. Therefore, Mahalanobisspaces can be formed at predetermined times from a data group of saidplurality of parameters measured at predetermined times. Therefore, byusing said Mahalanobis spaces formed at predetermined times, Mahalanobisdistances at predetermined times can be calculated from a group ofmeasured values of the plurality of parameters, obtained from theoperating condition of the semiconductor manufacturing equipment.

[0018] According to the present invention, there is provided amanagement system of semiconductor manufacturing equipment comprising:

[0019] a memory unit for storing data on a Mahalanobis space obtainedfrom a parameter showing a normal operating condition of semiconductormanufacturing equipment;

[0020] a detection mechanism for obtaining data values of said parameterfrom said semiconductor manufacturing equipment in operation;

[0021] an arithmetic circuit for calculating a Mahalanobis distance froma data group of said parameter, obtained by said detection mechanism byusing said Mahalanobis space stored in said memory unit; and

[0022] a circuit for deciding whether or not a calculated value of saidMahalanobis distance by said arithmetic circuit exceeds a predeterminedvalue.

[0023] According to the present invention, the arithmetic circuitcalculates a Mahalanobis distance from parameter values obtained by thedetection mechanism on the basis of a Mahalanobis space stored in thememory unit, and the decision circuit decides whether or not thecalculated Mahalanobis distance exceeds a predetermined value.Therefore, the method according to the present invention can be put intoquick and effective use.

[0024] The management system according to the present invention can beapplied to management of the plasma etching system. As a detectionmechanism for detecting plasma emission intensity of the plasma etchingsystem, it is possible to use a detection mechanism with a plasmaemission intensity detector that measures the intensity of a desiredwavelength of plasma emission of the etching system.

[0025] From data on plasma emission intensity detected by the plasmaemission intensity detector, it is possible to obtain theabove-mentioned Mahalanobis space and Mahalanobis distance. By decisionmade by using the Mahalanobis distance, it is possible to decide withhigh accuracy whether the plasma etching system has operated normally ornot.

[0026] The above-mentioned detection mechanism may be a detectionmechanism including a voltage detector and a current detector forobtaining a current value, a voltage value, and a phase of highfrequency output of a high frequency transmitter installed in the plasmaetching system. By using this detection mechanism, in other words, byusing data on the voltage value, the current value and the phase, theabove-mentioned Mahalanobis space and Mahalanobis distance can beobtained. By a decision made by using the Mahalanobis distance, it ispossible to decide with high accuracy whether the plasma etching systemhas operated normally or not.

[0027] The above-mentioned detection mechanism can further include adata converter for obtaining current values, voltage values and a phasefrom the fundamental wave and harmonics of the high frequency outputfrom a current value and a voltage value detected by the currentdetector and the voltage detector. Therefore, on the basis of data of aplurality of parameters, such as the current values, voltage values andthe phases of the fundamental wave and the harmonics at predeterminedtimes, Mahalanobis spaces can be generated at the predetermined times.Thus, by using the Mahalanobis spaces at the predetermined times,Mahalanobis distances can be calculated from measured values of theplurality of parameters, obtained under operating condition of theetching system.

[0028] Therefore, by converting the operating condition of the etchingsystem into time-series changes between data values by making a decisionabout the Mahalanobis distance generated in time series, the operatingcondition of the etching system can be managed suitably in time seriesaccording to the correlation among the parameters.

[0029] As the detection mechanism of the etching system, a detectionmechanism with an emission spectrometer may be used to measure theintensity of a plurality of desired wavelengths of plasma emission.

[0030] The emission spectrometer, being capable of measuring theintensity of a plurality of desired wavelengths, can handle thedifferent degrees of intensity of the plurality of wavelengths of plasmaemission as parameters. Therefore, it becomes possible to suitablymanage the operating condition of the etching system by time seriescontrol according to the correlation between the different degrees ofintensity of different wavelengths of plasma emission.

BRIEF DESCRIPTION OF THE DRAWINGS

[0031]FIG. 1 is a block diagram schematically showing a managementsystem of semiconductor manufacturing equipment according to the presentinvention;

[0032]FIG. 2 is a graph of light intensity showing an example of changesin data detected by the detection mechanism of the management systemdepicted in FIG. 1;

[0033]FIG. 3 is an explanatory diagram showing data for obtainingMahalanobis spaces used in the management system in FIG. 1;

[0034]FIG. 4 is an explanatory diagram showing a data processing methodfor obtaining Mahalanobis spaces;

[0035]FIG. 5 is a diagram, like in FIG. 1, schematically showing anotherexample of the management system of semiconductor manufacturingequipment according to the present invention;

[0036]FIG. 6 is an explanatory diagram showing a data group on aplurality of parameters detected by the detection mechanism of themanagement system in FIG. 5;

[0037]FIG. 7 is a graph (part 1) showing changes in the data grouppresented in FIG. 6;

[0038]FIG. 8 is a graph (part 2) showing changes in the data grouppresented in FIG. 6;

[0039]FIG. 9 is a graph (part 3) showing changes in the data grouppresented in FIG. 6;

[0040]FIG. 10 is a graph (part 4) showing changes in the data grouppresented in FIG. 6;

[0041]FIG. 11 is a graph showing changes in Mahalanobis distanceobtained by the management system in FIG. 5;

[0042]FIG. 12 is a diagram, like in FIG. 1, schematically showinganother example of the management system of semiconductor manufacturingequipment according to the present invention;

[0043]FIG. 13 is an explanatory diagram showing the data group on aplurality of parameters detected by the detection mechanism in FIG. 9;

[0044]FIG. 14 is a graph showing an example of a conventional EPDwaveform in semiconductor manufacturing equipment in FIG. 3; and

[0045]FIG. 15 is a graph showing changes in Mahalanobis distanceobtained by the management system of semiconductor manufacturingequipment in FIG. 13.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0046] <Embodiment 1>

[0047]FIG. 1 shows an example of application of the management system ofthe present invention to a plasma etching system as one of semiconductormanufacturing equipment.

[0048] As has been well known, a plasma etching system 11, to which amanagement system 10 of the present invention is applied, is used toperform dry etching, for example, to bore contact holes in a top layer12 a, such as an insulating film, formed on a semiconductor substrate12, such as a semiconductor wafer.

[0049] The plasma etching system 11, as shown in FIG. 1, includes ahousing 13, a reactor 14 for preserving plasma, accommodated in thehousing, a couple of electrodes 15 (15 a and 15 b) arranged spaced apartfrom each other in a reaction chamber 14 a defined in the reactor 14, ahigh frequency generator 16 as a high frequency source to produceplasma, and a controller 17 to control the operation of the units,including the high frequency generator 16 of the plasma etching system11.

[0050] One electrode 15 a is connected to earth ground, while the otherelectrode receives high-frequency output from the high frequencygenerator 16 through an impedance matching box 18.

[0051] A semiconductor substrate 12 is arranged, with the top layer 12 afacing up for processing, on the electrode 12 b that receives outputfrom the high frequency generator 16. As is well known, a selectiveetching mask is attached when necessary to the surface 12 a, which isprocessed, of the semiconductor substrate 12.

[0052] A reaction gas, such as CF₄, is guided to the reaction chamber 14a of the reactor 14 through a well-known gas Supply system, not shown,and the gas is discharged regularly through an exhaust system tomaintain the atmosphere in the reaction chamber 14 a at a desired gaspressure.

[0053] In the plasma etching system 11, as is well known, by theoperation of the controller 17, when high-frequency electric power isoutput from the high frequency generator 16 to the other electrode 15 b,plasma, containing active molecules and atoms called radicals, is formedby glow discharge between the electrodes 15 a and 15 b, and by chemicalreactions of radicals, the top layer 12 a of the semiconductor substrate12 is etched. RIE (reactive ion etching) may be applied preferably.

[0054] At this time, the plasma emission varies with the progress ofetching. In other words, the intensity of light of a desired wavelength,which increases with the progress of etching of the top layer 12 a as aninsulating layer different in material from the semiconductor layer 12,drops when the etching action extends to the semiconductor substrate 12under the top layer 12 a.

[0055] The changes in light intensity are shown in the graph of FIG. 2.

[0056] The horizontal axis of FIG. 2 represents time (in seconds) fromthe start of etching, and the vertical axis represents the lightintensity by plasma emission in the reaction chamber 14 a in the etchingprocess.

[0057] The characteristic curve 19 of FIG. 2 shows the changes in lightintensity of a given wavelength by plasma emission. As indicated by thischaracteristic curve 19, the intensity of plasma emission caused byetching of the top layer, which started at time 0, increases to Y′₁,Y′₂, then to Y′₃ with the progress of etching as time passes through X₁,X₂ and X₃.

[0058] When the plasma emission intensity is almost saturated (Y′₃) attime X₃, the emission intensity decreases with decrease in the thicknessof the top layer 12 a, and the emission intensity falls below a givenvalue Y′_(n) at time X_(n).

[0059] At this time, a decision can be made that etching has reached thesemiconductor substrate 12, and from this it can be known that requiredetching has ended for contact holes that pass through the top layer 12a.

[0060] The management system by which to detect the end of the etchingprocess by observing a light of a desired wavelength in plasma emissionis known as the EPD (End Point Detect) system.

[0061] The management system 10 according to the present invention iscapable of detecting whether or not a plasma etching system 11 operatednormally by observing a light of a desired wave in plasma emission.

[0062] Again referring to FIG. 1, the management system includes a lightsensor 20, installed in the reaction chamber 14 a, for detecting a lightintensity of a desired wavelength in plasma emission in the reactionchamber 14 a; and an information processing unit 22 for receiving asignal detected by the light sensor 20 through a monitor 21 andprocessing data of the signal.

[0063] The plasma emission shows a peak value in a desired range ofwavelengths, though the range differs with the active gas in thereaction chamber 14 a, the top layer 12 a to be etched, or otheroperating conditions. The light sensor 20, provided as a light intensitydetector of the light detection mechanism, includes a filter or amonochrometer for receiving light of the desired wavelength range, andthereby converts the light intensity of the desired wavelength rangeinto an electric signal, and sends it to the monitor 21.

[0064] On receiving an electric signal from the light sensor 20 as aplasma emission intensity detector, the monitor 21 detects a finish timeof etching from observation of the emission intensity as has beendescribed with reference to FIG. 2. The monitor 21 sends the electricsignal from the light sensor 20 to the information-processing unit 22.

[0065] The information-processing unit 22 comprises a computer in theexample shown in FIG. 2. The computer 22 includes a memory unit 23 forstoring data on Mahalanobis space to be described later, an arithmeticcircuit 24 for arithmetic operation of data represented by a parametersignal of light intensity detected by the light sensor 20 as a lightintensity detector, and a comparator 25.

[0066] The arithmetic circuit 24 and the comparator circuit 25 shouldpreferably be realized by software to achieve a desired arithmeticfunction, which will be described later.

[0067] Before the management system 10 according to the presentinvention is put into operation, a Mahalanobis space under normaloperating condition of the plasma etching system is generated.

[0068] To form this Mahalanobis space, the light sensor 20 detects theintensity of a desired wavelength in plasma emission in the process offorming etched holes.

[0069] By intensity detection by the light sensor 20, data on respectivedegrees of emission intensity (Y′₁, Y′₂, Y′₃, . . . Y′_(n)) is sampledat times (X₁, X₂, X₃, . . . X_(n)) shown in FIG. 2 in the process offorming etched holes in the top layer on a piece of semiconductorsubstrate 12.

[0070] Under normal operating condition, sampling is further done ondata, same as mentioned above, in the process of forming etched holeswith another semiconductor substrate 12. Consequently, with regard to asingle parameter under normal operating condition, in other words, withregard to the intensity of a desired wavelength in plasma emission inthis example, a data group can be obtained from etching processescarried out a plurality of times.

[0071]FIG. 3(a) shows a group of measured data obtained by sampling.Measured data is designated as y′_(1•1) . . . y′_(n•1) for respectivedegrees of emission intensity (Y′₁, Y′₂, Y′₃, . . . Y′_(n))in theetching process (1) on a given semiconductor substrate 12. Similarmeasured data of emission intensity is designated as y′_(1•2) . . .y′_(n•m) in an etching process (2 . . . m) on another semiconductorsubstrate 12 as given below.

[0072] The measured data (y′_(1•1) to y′_(1•m)) is standardized by usingthe following equation.

Y _(n•m)=(Y′ _(n•m) −Ave _(n))/σ_(n)  (1)

[0073] where Ave_(n) is an average of each measured data at times (X₁,X₂, X₃ . . . X_(n)). In other words, Ave₁ denotes an average of y′_(1•1). . . y′_(1•m). Similarly, Ave_(n) denotes y′_(n•1) . . . y′_(n•m).σ_(n) denotes a standard deviation of data at different times.

[0074]FIG. 3(b) shows a group of standardized data obtained bystandardizing the group of measured data shown in FIG. 3(a) by Eq.(1).

[0075] Arithmetic operations by Eq.(1) to obtain this group ofstandardized data can be performed by the arithmetic circuit 24 of thecomputer 22.

[0076] A correlation matrix R shown in FIG. 4(a) can be obtained from agroup of standardized data presented in FIG. 3(b). The matrix elementsr_(i•j) and r_(j•i) (i,j=1 to n) of the correlation matrix R can beexpressed as functions of data y_(i•j) and y_(j•i) of the group ofstandardized data as shown in Eq.(2) of FIG. 4(a).

[0077] When the correlation matrix R is obtained from the group ofstandardized data, an inverse matrix A of the correlation matrix R, thatis, a Mahalanobis space A (a base space A) under normal operatingcondition of the plasma etching system 11 can be obtained.

[0078] An arithmetic process to obtain this Mahalanobis space can becarried out entirely by the arithmetic circuit 24. The matrix elementsa_(i•j) (i,j=1 to n) of the inverse matrix A, or a Mahalanobis space A,are stored in the memory unit 23 of the computer 22.

[0079] After the Mahalanobis space A is obtained, when the plasmaetching system 11 is put into an ordinary operation for etching of asemiconductor substrate 12, just as mentioned above, data on theintensity of a desired wavelength is sampled through the light sensor 20from plasma emission in the reaction chamber 14 a of the plasma etchingsystem 11.

[0080] When a series of measured data y′₁ . . . y′_(n) is obtained bythe finish of the etching process of the semiconductor substrate 12, themeasured data undergoes the same standardization process as mentionedabove by Eq.(1) using Ave_(n) and σ_(n), by which a series ofstandardized data y₁ . . . y_(n) same as shown in FIG. 3(b) can beobtained.

[0081] When a series of standardized data is obtained, a Mahalanobisdistance D² can be obtained by execution of the arithmetic operation byEq.(3) as shown in FIG. 4(c).

[0082] The y_(i), y_(j) shown in Eq.(3) are values obtained fromstandardized data y₁ . . . y_(n). On the other hand, a_(i•j) is a matrixelement of the previously obtained Mahalanobis space A.

[0083] The Mahalanobis distance D² obtained by the arithmetic circuit 24comes to be a value closer to 1 when there is a higher similaritybetween a series of data y₁ . . . y_(n) as the basis for obtaining thisdistance and a group of base data y_(1•1) . . . y_(n•m) as the basis forobtaining the Mahalanobis space A.

[0084] In other words, so long as the Mahalanobis space A is generatedby a data group under normal operating condition of the plasma etchingsystem 11, the operating condition is closer to normal as theMahalanobis distance D²is closer to 1. Conversely, the operatingcondition deviates more from being normal as the Mahalanobis distance D²becomes more remote from 1.

[0085] Therefore, according to a decision by the comparator circuit 25as to whether or not the Mahalanobis distance D²is larger than athreshold value, it is possible to decide whether nor not the etchingprocess that gave a series of data y₁ . . . y_(n) ended normally.

[0086] When the comparator circuit 25 makes a abnormality decision,alarm means, such as a sound generator or an indicator lamp, not shown,can be actuated. The computer 22 can send an operation stop signal tothe controller 17 of the plasma etching system.

[0087] The threshold value mentioned above can be selected properlybetween 2 and 4, for example, according to strictness of control.

[0088] According to the control system 10 according to the presentinvention, a decision can be made for each etching process about whetheror not the etching process took place normally by using information fromthe light sensor of the EPD (End Point Detect) system that observesplasma emission of the plasma etching system. Thus, it is possible tocontrol the etching process properly.

[0089] An example of etching process control has been described. But,the management method according to the present invention can be appliedto abnormality detection at a start-up operation after periodicinspection or after overhauling of the plasma etching system 11.

[0090] To obtain a Mahalanobis space A from a data group under normaloperating condition at the start-up, an unprocessed siliconsemiconductor substrate, for example, may be used as a dummy specimeninstead of a semiconductor substrate 12.

[0091] A group of measured data, like those given in FIG. 3(a), onplasma emission is obtained by using this dummy specimen, from thisgroup of measured data, a group of standardized data like those given inFIG. 3(b) is obtained, and from this group of standardized data, aMahalanobis space under normal operating condition, like the onementioned above, is obtained.

[0092] In a subsequent start-up operation, from standardized dataobtained by standardizing measured data taken during the start-upoperation, a Mahalanobis distance D² like the one mentioned above isobtained.

[0093] Therefore, from the value of this Mahalanobis distance D², adecision can be made whether or not the start-up operation took placenormally.

[0094] In a case where a number of parameters are used, such as thepressure or the temperature in the reaction chamber 14 a, or the highfrequency output, Mahalanobis spaces (B, C, . . . ) can be previouslygenerated under multiple abnormal conditions, each abnormal conditionbeing set such that one of the parameters, the pressure for example, isset at an abnormal value, and the other parameters are set at normalordinary values.

[0095] When a decision was made that the plasma etching system 11 isoperating abnormally, by using a group of standardized data obtainedunder the operating condition judged abnormal and instead of theMahalanobis space A, on the basis of Mahalanobis spaces (B, C . . . )generated under mutually different abnormal operating conditions, eachabnormal operating condition having one parameter set at an abnormalvalue and the other parameters set at normal values, Mahalanobisdistances D² are obtained for the respective Mahalanobis spaces.

[0096] A Mahalanobis space (B, C . . . ) that gives the Mahalanobisdistance that is closest to 1 among all those Mahalanobis distances isconsidered to be under an operating condition closest to the operatingcondition judged abnormal.

[0097] Therefore, it is possible to estimate that abnormality would haveoccurred in the abnormal parameter used to derive the Mahalanobis space(B, C . . . ) that gives the Mahalanobis distance D² closest to 1. Inother words, when the Mahalanobis distance calculated on the basis of aMahalanobis space by setting the high frequency output at an abnormalvalue is closest to 1, the abnormal operating condition that gave thegroup of standardized data can be assumed which is attributable toabnormality in the high frequency output.

[0098] Therefore, the cause of abnormality can be assumed by comparingMahalanobis distances D² by using a Mahalanobis space under an abnormalparameter.

[0099] <Embodiment 2>

[0100] In the plasma etching systems, the high frequency output suppliedto the electrode 15 b from the high frequency generator 16 is highlyresponsive to changes in the impedance of the reaction chamber 14 a.Therefore, by detecting changes in high frequency electric power causedby changes in impedance, it is possible to know whether or not there isabnormality in the plasma etching system.

[0101] In the management system 10 shown in FIG. 5, a plurality ofparameters, including the voltage, the current and the phase of highfrequency electric power are adopted for operation management of theplasma etching system. To obtain data on those parameters, a detectionmechanism 20, including a voltage detector 20 a and a current detector20 b, is inserted between the impedance matching box 18 and theelectrode 15 b.

[0102] An electric signal (V) from the voltage detector 20 a and anelectric signal (I) from a current detector 20 b are input to a dataconverter 20 c.

[0103] On receiving the two electric signals (V, I), the data converter20 c, as shown in FIG. 6, outputs current values and voltage values anda phase of high frequency output of 13.56 MHz, for example, from thehigh frequency generator to the computer 22, more specifically, acurrent value 10 in the fundamental wave component and current valuesI₀, I₂, I₃, and I₄ in the first, second, third and fourth harmoniccomponents, a voltage value V₀ in the fundamental wave component andvoltage values V₁, V₂, V₃ and V₄ in the first, second and third andfourth harmonic components, and the phase Θ respectively at times (Time1, Time 2 . . . Time n).

[0104]FIG. 6 shows a data group to obtain a Mahalanobis space undernormal operating condition, which data has been standardized asmentioned above.

[0105] In the example of FIG. 6, to standardize data, standarddeviations σ of the current values I₀, I₁, I₂, I₃ and I₄, and thevoltage values V₁, V₂, V₃ and V₄ and the phase Θ at the measuring timeswere used. To obtain the averages Ave of those data, two sets of datawere used.

[0106] As shown in FIG. 6, by sampling data of a plurality of mutuallydifferent parameters from a plurality of specimens at the measuringtimes, and standardizing the data, a group of standardized data, whichcorresponds to a group of standardized data in FIG. 3(b), can beobtained at the measuring times.

[0107] From the groups of standardized data at the measuring times, acorrelation matrixR and a Mahalanobis space derived from the correlationmatrix R can be generated at the measuring times.

[0108] Therefore, as Mahalanobis spaces A are formed previously at themeasuring times, the arithmetic operation represented by Eq.(3) forcalculating a Mahalanobis distance D² at measuring times as mentionedabove can be executed successively at predetermined times from measureddata during the etching process as (current values I₀, I₂, I₃ and I₄,voltage values V₁, V₂, V₃ and V₄ and phase Θ). Thus, Mahalanobisdistances D₂ can be obtained at the measuring times.

[0109] FIGS. 7 to 11 are graphs showing examples of changes in measureddata (I₀, I₂, I₃, I₄, V₁, V₂, V₃, V₄ and the phase Θ) and changes in theMahalanobis distance D₂ in the second embodiment shown in FIG. 5.

[0110] This is a case where abnormality occurred in the operation of theplasma etching system 11 about 90 to 100 sec after the start of theetching process.

[0111] The horizontal axis of a graph in FIG. 7 represents time (sec)from the start to the end of etching, and the vertical axis representsvoltage values[V]. The characteristic curves 26 and 27 respectively showchanges in the voltage value V₀ of the fundamental wave component andthe voltage value V₁ of the first harmonic component of high frequencyoutput from the high frequency generator 16.

[0112] In the two characteristic curves 26 and 27, minute voltagechanges are observed which are considered to be noise, but in the graphof FIG. 7, there are no notable indications of change other than noise.

[0113] In the graph in FIG. 8, the horizontal axis represents time (sec)and the vertical axis represents voltage values (V) or current values(A). The characteristic curves 28, 29 and 30 in FIG. 8 show changes inthe voltage values V₂, V₃ and V₄ of the second, third and fourthharmonic components, while the characteristic curve 31 shows the currentvalue I₀ of the fundamental wave of the high frequency output.

[0114] On the characteristic curves 28 to 30, as with the characteristiccurves 26 and 27, there are voltage changes or current changes probablydue to noise, but no other changes can be found because of noise.

[0115] In the graph of FIG. 9, the horizontal axis represents time(sec), and the vertical axis represents current values (A). In FIG. 9,the characteristic curves 32 to 35 show changes in the current valuesI₁, I₂, I₃ and I₄ in the first, second, third and fourth harmoniccomponents of the high frequency output.

[0116] On the characteristic curve 32, a general sign of change isobserved slightly at a point in time about 100 sec from the start of theetching process, but this is not a distinctive change. As with thecharacteristic curve 32, on the characteristics curves 33 to 35including noise, changes other than noise can be found.

[0117] Meanwhile, in the graph in FIG. 10, in which the horizontal axisrepresents time (sec ) and the vertical axis represents phase angles(degrees), as is clear from changes of the characteristic curve 36showing changes in phase, though noise is included in the characteristiccurve 36, a distinctive change in phase angle can be observed.

[0118] However, as is apparent from the graph of FIG. 10, because thephase variation is no more than a phase change of 5° from about −50° toabout −45°, so that a large SIN ratio cannot be obtained.

[0119] In contrast, in the graph showing changes in Mahalanobis distanceD² in FIG. 11, a very large change can be observed clearly in the curveof Mahalanobis distance D².

[0120] In FIG. 11, the horizontal axis represents time (sec), and thevertical axis represents the Mahalanobis distance D².

[0121] The characteristic curve 37 was obtained by plotting at themeasuring times a Mahalanobis distance D² calculated on the basis ofMahalanobis spaces A formed at the measuring times and from measureddata (I₀, I₁, I₂, I₃, V₁, V₂, V₃, V₄ and the phase Θ) obtained at themeasuring times from the start to the end of the etching process.

[0122] Viewed by micro analysis, the characteristic curve 37 includes anoise component same as with the characteristic curves 26 to 36mentioned above. However, a very large change greater than changes owingto the noise component is observed at a point about 100 sec on the timebase.

[0123] More specifically, on the graph of FIG. 11, the characteristiccurve 37 shows that the Mahalanobis distance D² stays at a value closeto about zero (precisely 1) for some time, but rises sharply towardslevels of about 250.

[0124] Therefore, by setting a threshold value for the Mahalanobisdistance D² showing an abnormal value at 250, for example, it becomespossible to detect an abnormal condition by variations about 250 timesgreater than those during normal operating condition. Compared with acase where an abnormal operating condition is detected only by changesin phase as mentioned above, an abnormal operating condition can bedetected with a very high S/N ratio.

[0125] The above-mentioned threshold value for the Mahalanobis distanceD² can be selected at one's discretion, for example, it may be set at avalue of 1 or 50. Even if the threshold value is set at either of thosevalues, a malfunction of the plasma etching system 11 can be detectedaccurately with a higher S/N ratio than in abnormality detection only byphase.

[0126] According to the management system 10 in the second embodiment,as mentioned above, a decision can be made whether or not theMahalanobis distance D² is greater than a predetermined value at each ofthe data measuring times. By this arrangement, if abnormality occursduring etching of a semiconductor substrate 12, it can be detected atthe moment.

[0127] Accordingly, in response to abnormality detection, an alarm canbe issued or the plasma etching system 11 can be stopped immediately totake a quick action.

[0128] Also in the second embodiment, by having Mahalanobis distancesand spaces prepared previously under mutually different conditions, ineach of which one parameter is intentionally set at an abnormal valueand the other parameters are set at normal values, the Mahalanobisdistances and spaces can be used to deduce an abnormal parameter like inthe example described when the first embodiment was referred to.

[0129] <Embodiment 3>

[0130] In the management system 10, rays of a plurality of wavelengthsfrom emission of plasma in the reaction chamber 14 a of the plasmaetching system 11 are used as mutually different parameters, and theintensity of rays of different wavelengths are sampled as data.

[0131] As detection means 20 for obtaining data on a plurality ofdesired mutually different wavelengths from plasma emission in thereaction chamber 14 a, an optical fiber 20 is provided which guides therays from plasma in the reaction chamber 14 a to the outside of theplasma etching system 11. The plasma light led out through the opticalfiber 20 is guided to the emission spectrometer 21. The emissionspectrometer 21 outputs intensity peak values of the desired wavelengthstogether with data on the wavelengths to the arithmetic circuit 24.

[0132]FIG. 13 shows a data group for generating a Mahalanobis spaceunder normal operating condition, sampled by the emission spectrometer21. Presented in FIG. 13 is a data group that has been standardized bythe same standardizing process as mentioned above.

[0133] AS has been described referring to the second embodiment, in FIG.13 the data of a plurality of mutually different parameters was obtainedfrom a plurality of specimens. A group of standardized data can beobtained, which corresponds to the standardized data separately sampledat the measuring times in FIG. 3(b).

[0134] Therefore, from standardized data sampled at the measuring times,a correlation matrix R and a Mahalanobis space A derived from thecorrelation atrix R as shown in FIG. 4 can be generated at therespective data measuring times as in the second embodiment.

[0135]FIG. 14 is a graph showing changes in the intensity of theemission peak value of one wavelength, plotted by the conventionalmethod, in which the horizontal axis represents the lapsed time from thestart of etching and the vertical axis represents the emissionintensity.

[0136]FIG. 14 shows a case where abnormality occurred in the operationof the plasma etching system 11 at time T from the start of the etchingprocess. On the characteristic curve 38 showing changes in the intensityof the emission peak value only, no distinctive change can be seenaround time T.

[0137] On the other hand, the graph in FIG. 15 shows the relationbetween time in the above-mentioned case where abnormality occurred attime T and the Mahalanobis distance D². The characteristic curve 39shows changes in the Mahalanobis distance D² when peak values weresampled for wavelengths λ1, λ2, . . . λ11, Mahalanobis spaces weregenerated at the measuring times, derived from standardized data at themeasuring times, and Mahalanobis distances D² were generated at themeasuring times from measured data in the case where abnormalityoccurred at time T.

[0138] The characteristic curve 39 clearly shows a change in theMahalanobis distance D2 at about time T that reveals a notable change,which could not be observed on the characteristic curve 38 that onlyshows the emission intensity the graph in FIG. 15.

[0139] Therefore, the management system in the third embodiment iscapable of detecting an infinitesimal change in plasma in the reactionchamber 14 a of the plasma etching system 11, which cannot be detectedonly from a change in emission intensity. Therefore, it becomes possibleto manage the operation of the plasma etching system 11 with highaccuracy.

[0140] The foregoing description has been made using an opticalparameter related to plasma emission or electrical parameters, such asvoltage, current and phase of high frequency electric power in order tomanage the operation of the plasma etching system.

[0141] The present invention of this patent application is not limitedto them, it is possible to adopt various system parameters representingthe operating condition of the plasma etching system, such as gaspressure, APC, or the like of the reaction chamber of the plasma etchingsystem by using a detector, such as a mass spectrograph.

[0142] Besides the above-mentioned management of the plasma etchingsystem, the management method according to the present invention can beapplied to management of other semiconductor manufacturing equipment.

[0143] According to the management method of the present invention, asmentioned above, a plurality of data of a data group are not handledindependently, but handled in data groups, and a decision is madewhether the semiconductor manufacturing equipment is operating normallyor not on the basis of a Mahalanobis space which takes correlationbetween data into consideration. Therefore, it is possible to manage theoperating condition of the semiconductor manufacturing equipment withhigh accuracy unobtainable with the conventional interlock system whichdoes not consider correlation between data.

[0144] According to the management system of the present invention, asdescribed above, the arithmetic circuit calculates a Mahalanobisdistance from parameter values obtained by the detection mechanism onthe basis of a Mahalanobis space stored in the memory unit, and thedecision circuit decides whether or not the calculated Mahalanobisdistance exceeds a predetermined value. Therefore, the method accordingto the present invention can be put into quick and effective use, sothat the operation of the semiconductor manufacturing equipment can bemanaged with a system of relatively simple configuration.

What is claimed is:
 1. A method of managing the operation ofsemiconductor manufacturing equipment comprising the steps of: samplinga plurality of data of at least one parameter under a normal operatingcondition of said semiconductor manufacturing equipment; generating aMahalanobis space on the basis of a group of sampled data; calculating,on the basis of said Mahalanobis space, a Mahalanobis distance from agroup of measured values of said parameters under the actual operatingcondition of said semiconductor manufacturing equipment; and when acalculated Mahalanobis distance exceeds a predetermined value, making adecision that a malfunction occurred in said semiconductor manufacturingequipment.
 2. A management method according to claim 1, furthercomprising the steps of: sampling a plurality of data under abnormalconditions each abnormal condition being generated by setting oneparameter at an abnormal value and other said parameters at normalvalues; generating Mahalanobis spaces under said abnormal conditions;when, from a value of said Mahalanobis distance, a decision has beenmade that a malfunction occurred, calculating Mahalanobis distancescorresponding to Mahalanobis spaces from said measured values, on thebasis of said Mahalanobis space under the abnormal condition; andestimating that among said plurality of parameters, abnormality occurredin a parameter that gave a Mahalanobis space such that said Mahalanobisdistance is closest to
 1. 3. A management method according to claim 1,wherein said at least one parameter is a plurality of mutually differentparameters, said management method further comprising generatingMahalanobis spaces at predetermined times from a data group of saidplurality of parameters measured at predetermined times, and calculatingMahalanobis distances at predetermined times from a group of measuredvalues of said plurality of parameters, obtained from the operatingcondition of said semiconductor manufacturing equipment by using saidMahalanobis spaces formed at predetermined times.
 4. A management systemof semiconductor manufacturing equipment comprising: a memory unit forstoring data on a Mahalanobis space obtained from a parameter showing anormal operating condition of semiconductor manufacturing equipment; adetection mechanism for obtaining data values of said parameter fromsaid semiconductor manufacturing equipment in operation; an arithmeticcircuit for calculating a Mahalanobis distance from a data group of saidparameter, obtained by said detection mechanism by using saidMahalanobis space stored in said memory unit; and a circuit for decidingwhether or not a calculated value of said Mahalanobis distance by saidarithmetic circuit exceeds a predetermined value.
 5. A management systemaccording to claim 4, wherein said semiconductor manufacturing equipmentis a plasma etching system utilizing plasma emission, and wherein saiddetection mechanism is a plasma emission intensity detector formeasuring the intensity of a desired wavelength of the plasma emissionof said etching system.
 6. A management system according to claim 4,wherein said semiconductor manufacturing equipment is a plasma etchingsystem equipped with a high frequency oscillator for plasma emission,and wherein said detection mechanism includes a current detector and avoltage detector for obtaining a current value, a voltage value, and aphase of high frequency output of said high frequency oscillator.
 7. Amanagement system according to claim 6, wherein said detection mechanismfurther includes a data converter for calculating current values,voltage values and phases of a fundamental wave and harmonics of saidhigh frequency output, from a current value and a voltage value detectedby said current detector and said voltage detector.
 8. A managementsystem according to claim 4, wherein said semiconductor manufacturingequipment is a plasma etching system utilizing plasma emission, andwherein said detection mechanism further includes an emissionspectrometer for measuring the intensity of a plurality of desiredwavelengths of plasma emission of said etching system.